JPEG 2000 code streams are regions of interest that offer several mechanisms to support spatial random access or region of interest access at varying degrees of granularity. It is possible to store different parts of the same picture using different quality.

As of 2018, there are very few digital cameras that encode photos in the JPEG 2000 format, and many applications for viewing and editing photos still do not support it.[citation needed]

While there is a modest increase in compression performance of JPEG 2000 compared to JPEG, the main advantage offered by JPEG 2000 is the significant flexibility of the codestream. The codestream obtained after compression of an image with JPEG 2000 is scalable in nature, meaning that it can be decoded in a number of ways; for instance, by truncating the codestream at any point, one may obtain a representation of the image at a lower resolution, or signal-to-noise ratio – see scalable compression. By ordering the codestream in various ways, applications can achieve significant performance increases. However, as a consequence of this flexibility, JPEG 2000 requires encoders/decoders that are complex and computationally demanding. Another difference, in comparison with JPEG, is in terms of visual artifacts: JPEG 2000 only produces ringing artifacts, manifested as blur and rings near edges in the image, while JPEG produces both ringing artifacts and 'blocking' artifacts, due to its 8×8 blocks.

JPEG 2000 has been published as an ISO standard, ISO/IEC 15444. As of 2017[update], JPEG 2000 is not widely supported in web browsers, and hence is not generally used on the Internet.

At high bit rates, artifacts become nearly imperceptible, so JPEG 2000 has a small machine-measured fidelity advantage over JPEG. At lower bit rates (e.g., less than 0.25 bits/pixel for grayscale images), JPEG 2000 has a significant advantage over certain modes of JPEG: artifacts are less visible and there is almost no blocking. The compression gains over JPEG are attributed to the use of DWT and a more sophisticated entropy encoding scheme.

JPEG 2000 decomposes the image into a multiple resolution representation in the course of its compression process. This pyramid representation can be put to use for other image presentation purposes beyond compression.

These features are more commonly known as progressive decoding and signal-to-noise ratio (SNR) scalability. JPEG 2000 provides efficient code-stream organizations which are progressive by pixel accuracy and by image resolution (or by image size). This way, after a smaller part of the whole file has been received, the viewer can see a lower quality version of the final picture. The quality then improves progressively through downloading more data bits from the source.

Like the Lossless JPEG standard,[1] the JPEG 2000 standard provides both lossless and lossy compression in a single compression architecture. Lossless compression is provided by the use of a reversible integer wavelet transform in JPEG 2000.

The aim of JPEG 2000 is not only improving compression performance over JPEG but also adding (or improving) features such as scalability and editability. JPEG 2000's improvement in compression performance relative to the original JPEG standard is actually rather modest and should not ordinarily be the primary consideration for evaluating the design. Very low and very high compression rates are supported in JPEG 2000. The ability of the design to handle a very large range of effective bit rates is one of the strengths of JPEG 2000. For example, to reduce the number of bits for a picture below a certain amount, the advisable thing to do with the first JPEG standard is to reduce the resolution of the input image before encoding it. That is unnecessary when using JPEG 2000, because JPEG 2000 already does this automatically through its multiresolution decomposition structure. The following sections describe the algorithm of JPEG 2000.

According to KB, «the current JP2 format specification leaves room for multiple interpretations when it comes to the support of ICC profiles, and the handling of grid resolution information».[20]

Initially images have to be transformed from the RGB color space to another color space, leading to three components that are handled separately. There are two possible choices:

Irreversible Color Transform (ICT) uses the well known YCBCR color space. It is called "irreversible" because it has to be implemented in floating or fix-point and causes round-off errors.

Reversible Color Transform (RCT) uses a modified YUV color space that does not introduce quantization errors, so it is fully reversible. Proper implementation of the RCT requires that numbers are rounded as specified that cannot be expressed exactly in matrix form. The transformation is:

The chrominance components can be, but do not necessarily have to be, down-scaled in resolution; in fact, since the wavelet transformation already separates images into scales, downsampling is more effectively handled by dropping the finest wavelet scale. This step is called multiple component transformation in the JPEG 2000 language since its usage is not restricted to the RGB color model.

After color transformation, the image is split into so-called tiles, rectangular regions of the image that are transformed and encoded separately. Tiles can be any size, and it is also possible to consider the whole image as one single tile. Once the size is chosen, all the tiles will have the same size (except optionally those on the right and bottom borders). Dividing the image into tiles is advantageous in that the decoder will need less memory to decode the image and it can opt to decode only selected tiles to achieve a partial decoding of the image. The disadvantage of this approach is that the quality of the picture decreases due to a lower peak signal-to-noise ratio. Using many tiles can create a blocking effect similar to the older JPEG 1992 standard.

irreversible: the CDF 9/7 wavelet transform. It is said to be "irreversible" because it introduces quantization noise that depends on the precision of the decoder.

reversible: a rounded version of the biorthogonal CDF 5/3 wavelet transform. It uses only integer coefficients, so the output does not require rounding (quantization) and so it does not introduce any quantization noise. It is used in lossless coding.

After the wavelet transform, the coefficients are scalar-quantized to reduce the number of bits to represent them, at the expense of quality. The output is a set of integer numbers which have to be encoded bit-by-bit. The parameter that can be changed to set the final quality is the quantization step: the greater the step, the greater is the compression and the loss of quality. With a quantization step that equals 1, no quantization is performed (it is used in lossless compression).

The result of the previous process is a collection of sub-bands which represent several approximation scales. A sub-band is a set of coefficients—real numbers which represent aspects of the image associated with a certain frequency range as well as a spatial area of the image.

The quantized sub-bands are split further into precincts, rectangular regions in the wavelet domain. They are typically sized so that they provide an efficient way to access only part of the (reconstructed) image, though this is not a requirement.

Precincts are split further into code blocks. Code blocks are located in a single sub-band and have equal sizes—except those located at the edges of the image. The encoder has to encode the bits of all quantized coefficients of a code block, starting with the most significant bits and progressing to less significant bits by a process called the EBCOT scheme. EBCOT here stands for Embedded Block Coding with Optimal Truncation. In this encoding process, each bit plane of the code block gets encoded in three so-called coding passes, first encoding bits (and signs) of insignificant coefficients with significant neighbors (i.e., with 1-bits in higher bit planes), then refinement bits of significant coefficients and finally coefficients without significant neighbors. The three passes are called Significance Propagation, Magnitude Refinement and Cleanup pass, respectively.

Clearly, in lossless mode all bit planes have to be encoded by the EBCOT, and no bit planes can be dropped.

The bits selected by these coding passes then get encoded by a context-driven binary arithmetic coder, namely the binary MQ-coder. The context of a coefficient is formed by the state of its nine neighbors in the code block.

The result is a bit-stream that is split into packets where a packet groups selected passes of all code blocks from a precinct into one indivisible unit. Packets are the key to quality scalability (i.e., packets containing less significant bits can be discarded to achieve lower bit rates and higher distortion).

Packets from all sub-bands are then collected in so-called layers. The way the packets are built up from the code-block coding passes, and thus which packets a layer will contain, is not defined by the JPEG 2000 standard, but in general a codec will try to build layers in such a way that the image quality will increase monotonically with each layer, and the image distortion will shrink from layer to layer. Thus, layers define the progression by image quality within the code stream.

The problem is now to find the optimal packet length for all code blocks which minimizes the overall distortion in a way that the generated target bitrate equals the demanded bit rate.

While the standard does not define a procedure as to how to perform this form of rate–distortion optimization, the general outline is given in one of its many appendices: For each bit encoded by the EBCOT coder, the improvement in image quality, defined as mean square error, gets measured; this can be implemented by an easy table-lookup algorithm. Furthermore, the length of the resulting code stream gets measured. This forms for each code block a graph in the rate–distortion plane, giving image quality over bitstream length. The optimal selection for the truncation points, thus for the packet-build-up points is then given by defining critical slopes of these curves, and picking all those coding passes whose curve in the rate–distortion graph is steeper than the given critical slope. This method can be seen as a special application of the method of Lagrange multiplier which is used for optimization problems under constraints. The Lagrange multiplier, typically denoted by λ, turns out to be the critical slope, the constraint is the demanded target bitrate, and the value to optimize is the overall distortion.

Packets can be reordered almost arbitrarily in the JPEG 2000 bit-stream; this gives the encoder as well as image servers a high degree of freedom.

Already encoded images can be sent over networks with arbitrary bit rates by using a layer-progressive encoding order. On the other hand, color components can be moved back in the bit-stream; lower resolutions (corresponding to low-frequency sub-bands) could be sent first for image previewing. Finally, spatial browsing of large images is possible through appropriate tile and/or partition selection. All these operations do not require any re-encoding but only byte-wise copy operations.

Compared to the previous JPEG standard, JPEG 2000 delivers a typical compression gain in the range of 20%, depending on the image characteristics. Higher-resolution images tend to benefit more, where JPEG-2000's spatial-redundancy prediction can contribute more to the compression process. In very low-bitrate applications, studies have shown JPEG 2000 to be outperformed[21] by the intra-frame coding mode of H.264. Good applications for JPEG 2000 are large images, images with low-contrast edges — e.g., medical images.

JPEG2000 is much more complicated in terms of computational complexity in comparison with JPEG standard. Tiling, color component transform, discrete wavelet transform, and quantization could be done pretty fast, though entropy codec is time consuming and quite complicated. EBCOT context modelling and arithmetic MQ-coder take most of the time of JPEG2000 codec.

On CPU the main idea of getting fast JPEG2000 encoding and decoding is closely connected with AVX/SSE and multithreading to process each tile in separate thread. The fastest JPEG2000 solutions utilize both CPU and GPU power to get high performance benchmarks.[22][23]

Similar to JPEG-1, JPEG 2000 defines both a file format and a code stream. Whereas JPEG 2000 entirely describes the image samples, JPEG-1 includes additional meta-information such as the resolution of the image or the color space that has been used to encode the image. JPEG 2000 images should — if stored as files — be boxed in the JPEG 2000 file format, where they get the .jp2 extension. The part-2 extension to JPEG 2000, i.e., ISO/IEC 15444-2, also enriches this file format by including mechanisms for animation or composition of several code streams into one single image. Images in this extended file-format use the .jpx extension.

There is no standardized extension for code-stream data because code-stream data is not to be considered to be stored in files in the first place, though when done for testing purposes, the extension .jpc or .j2k appear frequently.

For traditional JPEG, additional metadata, e.g. lighting and exposure conditions, is kept in an application marker in the Exif format specified by the JEITA. JPEG 2000 chooses a different route, encoding the same metadata in XML form. The reference between the Exif tags and the XML elements is standardized by the ISO TC42 committee in the standard 12234-1.4.

World Meteorological Organization has built JPEG 2000 Compression into the new GRIB2 file format. The GRIB file structure is designed for global distribution of meteorological data. The implementation of JPEG 2000 compression in GRIB2 has reduced file sizes up to 80%.[24]

The PNG (Portable Network Graphics) format is still more space-efficient in the case of images with many pixels of the same color[citation needed], such as diagrams, and supports special compression features that JPEG 2000 does not.

JPEG 2000 is covered by patents, but the contributing companies and organizations agreed that licenses for its first part—the core coding system—can[clarification needed] be obtained free of charge from all contributors.

The JPEG committee has stated:

It has always been a strong goal of the JPEG committee that its standards should be implementable in their baseline form without payment of royalty and license fees... The up and coming JPEG 2000 standard has been prepared along these lines, and agreement reached with over 20 large organizations holding many patents in this area to allow use of their intellectual property in connection with the standard without payment of license fees or royalties.[25]

However, the JPEG committee has acknowledged that undeclared submarine patents may still present a hazard:

It is of course still possible that other organizations or individuals may claim intellectual property rights that affect implementation of the standard, and any implementers are urged to carry out their own searches and investigations in this area.[26]

In 2005, a JPEG 2000 based image browsing protocol, called JPIP has been published as ISO/IEC 15444-9.[29] Within this framework, only selected regions of potentially huge images have to be transmitted from an image server on the request of a client, thus reducing the required bandwidth.

JPEG 2000 data may also be streamed using the ECWP and ECWPS protocols found within the ERDAS ECW/JP2 SDK.

Motion JPEG 2000, (MJ2), originally defined in Part 3 of the ISO Standard for JPEG2000 (ISO/IEC 15444-3:2002,) as a standalone document, has now been expressed by ISO/IEC 15444-3:2002/Amd 2:2003 in terms of the ISO Base format, ISO/IEC 15444-12 and in ITU-T Recommendation T.802.[30] It specifies the use of the JPEG 2000 format for timed sequences of images (motion sequences), possibly combined with audio, and composed into an overall presentation.[31][32] It also defines a file format,[33] based on ISO base media file format (ISO 15444-12). Filename extensions for Motion JPEG 2000 video files are .mj2 and .mjp2 according to RFC 3745.

It is an open ISO standard and an advanced update to MJPEG (or MJ), which was based on the legacy JPEG format. Unlike common video formats, such as MPEG-4 Part 2, WMV, and H.264, MJ2 does not employ temporal or inter-frame compression. Instead, each frame is an independent entity encoded by either a lossy or lossless variant of JPEG 2000. Its physical structure does not depend on time ordering, but it does employ a separate profile to complement the data. For audio, it supports LPCM encoding, as well as various MPEG-4 variants, as "raw" or complement data.[34]

JP2 and JPX files containing GMLJP2 markup can be located and displayed in the correct position on the Earth's surface by a suitable Geographic Information System (GIS), in a similar way to GeoTIFF images.